Object and pose recognition are fundamental aspects of robot operation. However these operations tend to be resource-intensive and robots are typically resource-constrained. A general purpose robot may be called upon to act upon a plethora of different object types in myriad poses. It may not be feasible for the robot to store locally all of the object models and/or other data/routines needed to classify all possible objects and respective possible poses. Moreover, applying a large number of object models to each unclassified object observed in an environment may overwhelm the robot's resources, e.g., causing the robot to behave sluggishly, unresponsively, and/or erratically.